Hamilton Porter is proud to support the hiring needs, of one of the leaders in small business refinancing. Our long time client, is looking for a Data Scientist.
Location: Hybrid - Arlington, VA
Will develop models to support programs for the organization. Will classify or categorize data to make predictions related to the models.
What You Will Do:
Model Development:
- Design, develop, and deploy machine learning models and algorithms to solve business problems or improve processes for Legal/Collections and Sales
- Build models to classify account transaction data to benefit underwriting process and merchant insights
- Build models including but not limited to credit risk, fraud, and offer acceptance propensity
- Perform through testing and validation of models and support various aspects of the business with data analytics, i.e., experience with data and model governance
- Research, design, implement and validate cutting-edge algorithms/models to analyze diverse sources of data to achieve targeted outcomes, i.e., be up to date on data science research (papers and libraries); be able to build and evaluate models yourself
Advanced Data Analysis:
- Conduct sophisticated analysis on top of models to derive meaningful insights and actionable strategy recommendations.
- Identify new data sources and patterns that add lift to predictive modeling capabilities; come in with existing knowledge about relevant datasets and services to leverage
- Conduct analysis and turn insights into actionable changes for predictive models or policies; have experience identifying and prioritizing the business impact
Statistical Analysis:
- Apply statistical techniques to interpret data, validate models, and ensure robustness of analytical solutions.
- Deliver informative and effective findings, results and recommendations from statistical analysis to stakeholders, both technical and non-technical audiences
- Recommend ongoing improvements to methods and algorithms currently in production
Collaboration:
- Work closely with cross-functional teams such as engineering, product management, and business stakeholders to understand requirements and deliver solutions.
What We’re Looking For:
- MS in Statistics, Economics, Finance, or other related quantitative field
- Strong understanding of Computer Science fundamentals
- 3-5 years of relevant experience in applying data science techniques to real-world problems
- Strong proficiency Python and SQL for data manipulation, analysis, and modeling
- Econometric modeling, traditional modeling techniques (regression, tree-based models), deep learning, Natural Language Processing (NLP)
- Agile, Scrum experience
- Strong SQL
- Big data; experience with Databricks or Snowflake, Linux, AWS
- Strong understanding of Software Development Lifecycle (SDLC)
- Experience with exploratory data analysis and visualization
- Solid understanding of statistical methods and their application in data analysis and modeling
- Experience with machine learning techniques and libraries/frameworks (e.g., scikit-learn)
- Ability to work with large, complex datasets using tools like Pandas, Spark, or similar
- Strong analytical and problem-solving skills to translate business requirements into technical solutions
- Able to share a portfolio (e.g., website, github, paper references, etc.) of papers, visualizations, or software
- Excellent communication skills to articulate findings and insights to both technical and non-technical stakeholders.
Compensation:
- Competitive base salary ($110K - $124K - DOE) + potential for 10% performance bonus
- Outstanding company covered Health Coverage - tons of options across Health, Dental, Vision options + Flexible PTO
- 401K through Fidelity with 25% match
- Tons of other company wide perks...
Apply today we are quick to interview.
